Evidence map›Paper›PMID 33977218›Full record

ReviewDigital biomarkers

Evaluation, Acceptance, and Qualification of Digital Measures: From Proof of Concept to Endpoint.

Jennifer C Goldsack, Ariel V Dowling, David Samuelson, Bray Patrick-Lake, Ieuan Clay

Abstract readReview
In one paragraph

Review in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  18. Digital therapeutics in the clinic.Bioengineering & translational medicine · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jennifer C GoldsackDigital Medicine Society (DiMe), Boston, Massachusetts, USA.
Ariel V DowlingTakeda Pharmaceuticals Inc., Cambridge, Massachusetts, USA.
David SamuelsonEvidation Health Inc., San Mateo, California, USA.
Bray Patrick-LakeEvidation Health Inc., San Mateo, California, USA.
Ieuan ClayEvidation Health Inc., San Mateo, California, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To support the successful adoption of digital measures into internal decision making and evidence generation for medical product development, we present a unified lexicon to aid communication throughout this process, and highlight key concepts including the critical role of participant engagement in development of digital measures. We detail the steps of bringing a successful proof of concept to scale, focusing on key decisions in the development of a new digital measure: asking the right question, optimized approaches to evaluating new measures, and whether and how to pursue qualification or acceptance. Building on the V3 framework for establishing verification and analytical and clinical validation, we discuss strategic and practical considerations for collecting this evidence, illustrated with concrete examples of trailblazing digital measures in the field.

Indexed as

AcceptanceDigital endpointsDigital measuresPatient centricityQualificationV3

Identifiers

PMID33977218
PMCPMC8077605

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.